This relates to frame rate conversion which changes the frame rate of an input video stream. To increase the frame rate, missing frames are reconstructed when needed by duplicating existing frames or interpolating from existing frames.
When a video scene includes significant moving objects, the human visual system tracks their motion. When the frame rate conversion operation uses frame duplication, the location of the objects in consecutive frames does not change smoothly, interfering with the human visual tracking system. This interference causes a sense of jumpy, non-continuous motion called “judder.”
A significant motion causes a larger gap between the expected position and the actual position of the image in the series of frames, producing a larger judder artifact. Motion compensated frame rate conversion uses motion analysis of the video sequence to achieve high quality interpolation. Motion estimation involves analyzing previous frames and next frames to identify areas that have not moved. The accuracy of motion estimation is important for the quality of the output video stream. Motion compensation involves using motion vectors to predict picture element values. However, motion estimation algorithms are not perfect and motion compensation needs to have a mechanism to measure the quality of motion estimation and to be able to handle motion estimation errors.